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Tuesday, May 12, 2009

Reflections from PI’s economics conference, May 1-4 2009

Lee Smolin summarizes his impressions:My most lasting impression is that there is a growing field of research, which is at a stage where it could advance rapidly. Good work has been done over the last several decades, which has given us a store of results, hypotheses, conjectured laws and principles, methods etc which provide a good foundation for continued work. But much remains to be done before there can be a claim that these results add up to an approach to economic theory and modeling that can take over from the neoclassical paradigm as the foundation of economic theory.

To say that there is a field of research is not the same as saying that there is a theory or approach that everyone agrees on. Quite the opposite, what we saw was several distinct strands of thought, each with their own methodology, some of which were meeting each other for the first time. There is no consensus about the right way to approach economics out of equilibrium, even among those who take this as their goal. Even within approaches that share a common methodology, such as agent based models, we saw at least three very different frameworks based on different philosophies as to how agents are modeled and what the aim is. What makes it possible to group these diverse projects within a single field is so far only that they share a common aim, which is to develop an approach to economics which is dynamical and capable of describing markets out of equilibrium. For this goal to succeed it is not necessary that these directions become part of an eventual successful theory. But at least some of us suspect that there are latent and possibly important relationships between some of the directions, such as agent based models, insights from biology and the gauge theoretic approach. If this is right then there is a great deal to be gained from cross talk and collaboration amongst these approaches.

What should this field, which aims to be go beyond the study of equilibrium economics, be called? The term econophysics is useful but not general enough as we are not all physicists. Leigh Tesfatsion uses the term “non-equilibrium dynamical model (NED).” One possibility would be to shorten this to dynamical economics, as dynamical implies that it can encompass both non-equilibriium and equilibrium.

Another alternative is nonequilibrium economics, but this recalls the confusion between physicists and economists notions of equilibrium, due to the suggestion that the economists notion of equilibrium may correspond to a physicists’ notion of non-equilibrium steady state. Dynamical brings to mind the neoclassical conception of equilibrium as analogous to a static balance of forces. It encompasses everything having to do with the dynamics of an economy, ie with evolution in time. This includes agent based models and the gauge theoretic approaches.

Leigh Tesfatsion’s definition of NED I believe applies:

“A model of an economic system is an NED model if and only if the model generates the motion of the economic state between at least two **distinct** time points without dependence on external coordination conditions ("skyhooks"), i.e., coordination conditions imposed outside of any structural conditions, institutional arrangements, and behaviors arising from within the modeled economy.”

The biggest question that I am left with from the conference is whether there can be unification or at least cross talk amongst different approaches that could be so characterized. A possible route to this would be a unifying idea. Here is a candidate for one: the notion of path dependence in economic dynamics. This comes from the ecological and complex systems approaches to economics, as cycles are central to those programs, through Morowitz’s 1968 cycle theorem. We saw evidence for the importance of cycles in Kelly John Rose’s presentation and there were hints of it in some of the discussions of agent based models.

Path dependence is also the central idea of the gauge theory, as discussed by Pia Malaney and Eric Weinstein. The key insight of the gauge theory approach is that evolution of a market in time is generically path dependent, as a consequence of embodying in the mathematics the decomposition of a history of a portfolio or inventory into components of substitution, during which value doesn’t change, and growth, during which it does. This is the definition of what mathematicians call a connection. The efficient market hypothesis characterizes equilibrium as equivalent to path independence, which is in turn related to no-arbitrage. Hence, the evolution out of and fluctuations around equilibrium are path dependent, hence they are measured by what mathematicians call curvatures of the gauge connection. That is, in a gauge system the observables are connected with cycles; what they measure is path dependence around closed curves. This way of looking at it suggest that gauge invariance is a deep notion that underlies the dynamics of economics out of equilibrium, but the proof must be in what results this leads to.

Could the notion of gauge invariance be helpful for agent-based approaches? This is a step towards investigating the power of the notion of path dependence. This has been the particular interest of our small PI effort, with Sam Vazquez, Simone Severini and others, and what we have found is that gauge invariance can be imposed on agent based models and it helps to constrain the freedom in the choice of dynamics and point to interesting observables for measuring departures from equilibrium. Big questions remain such as whether the gauge invariance should be fundamental, or should be emergent, say when price discovery happens.

Another way to seek to bring the approaches together is to articulate common goals. Here is an attempt to do that:

Main goals of this field.

Develop a new theory of economics which extends neoclassical economics by discovering principles and laws which govern the dynamics of economies and markets.

Build a suite of toy models to illustrate and test these principles. These will be primarily agent based models, but they will be supported and checked by various analytic approximations.

Build a family of increasingly more realistic models to be compared to real markets, against real data. This is the goal of the test-bed that Leigh talks about. Develop a common format and language for both the toy and more realistic models and make them modular and open source, so that different researchers and groups may contribute their own ideas and models within the overall project.

Develop a family of data sets which can be used to test models against, and make them available in a common format for download from a project web page. It would be good if this data set encompasses several if not many countries as well as as long a time span as is practicable. As Danny Goroff emphasized, the construction, formatting and maintanence of these data sets are major efforts in themselves. Another point, raised by Sabine Hossenfelder, is that it would be very good to develop visualization tools to help in working with the data sets.

After sufficient development of models and testing against data sets the goal is the construction of tools for policy makers which might then be used “in the basements of central banks.”

Finally, integrate these newer approaches to economics with neoclassical economics, as the former, to the extent that they succeed, represent a deepening of the latter and are built on it rather than in opposition to it.

These goals are interconnected and it is likely that major progress in any of them will go hand in hand with progress in the others. A great deal has been done with agent based models, and, as Doyne Farmer emphasized, some laws and hypotheses are known. But I don’t think it is the case that there is yet a principle based theory of the dynamics of economics on the same level of robustness and canonicalness of the neoclassical theory of economic equilibrium.

A final way to seek to connect approaches is through common questions, so this is my last list.

Some key issues going forward from the conference

Here are the issues we wrote down on the board during the last morning as well as some which have been mentioned or occurred to me since. I would invite others to contribute their own.

What is the important data to explain/match? Where can it be found, how easy is it to get? Does there need to be work to define data sets and make them available online in specified formats?

Can we specify the minimal elements a model must have to be considered an “in principle” model of a market or an economy.

Can we specify the minimal elements a model must have to have the possibility of modeling a real world modern economy?

Can we define a framework, test-bed, set of protocols etc to define a class of economic models to allow them to be interchanged and developed efficiently?

What are the observables of an economic model? Are there unobvious observables? Are all the things in models genuinely observable? Are there non-obvious observables such as those associated with cycles? Is it a problem that many economic models/theories have elements such as utilities that are not observable? The notion of gauge invariance strongly constrains the choice of observables in physics, will it play a similarly powerful role in picking out the observables of economics?

What is the role of unobservables in economic models, such as utilities? Can models be constructed without them? Or, is there a necessary place in the model to represent the large variability in how real people and corporations make decisions, which are not readable off the economic data? That is, is it possible that the utilities represent factors that are and will remain unknown to the theorist that do influence market decisions? The goal of an economic theory and models may then be to understand and model a system, within the constraint that a component of the causes for decisions are unobservable to the modeler, because they are in the heads of the people involved?

What are the goals of economic modeling? Given Taleb’s point that we cannot hope to predict unusual events that have strong influence on markets, are there still questions that can be answered and patterns that can be found and understood? Can we investigate questions such as how to construct more or less stable markets, or possible tradeoffs between rate of growth and stability, without being able to predict exactly how a market will evolve?

What is the role of cycles in economic models? How relevant is Morowitz’s cycle theorem? A common theme of diverse approaches to non-equilibrium economics is path dependence. This arises in cycles in models of complex economies, including Kelly John Rose’s model of the US economy, it is also the key point in the application of gauge fields to economics. Is the role of cycles and path dependence a key insight which provides the basis for a unification of these diverse approaches?

Would it be interesting and novel to develop agent based models of trade among many countries? What questions could such models investigate? Would it be good to see if a dynamical economics approach could confirm or correct the principle of comparative advantage?

The role of innovation, technological development etc, appear to offer opportunities and challenges for theories of economics. They are good challenges because innovation is at the same time central to economic growth and impossible to predict in detail.

To what extent is market regulation a computer science problem? Given that all the major markets are instantiated in software and run across computer networks, can we conceive of the goal of stable markets, regulated as well as designed to be self-stablizing, which contribute to economic growth without being parasitic on it, as a design problem in computer science. Could we make use of experience computer scientists have of designing stable, dynamic networks?

Can we give meaning to the slogan, “economics is the continuation of natural selection by other means”? One hypothesis is that when accounting is invented there comes into existence a new entity, called the economic agent, which the books refer to. Whether this is an individual, family or a firm, it has specific existence and properties by virtue of the fact that books are kept of its activities. Is it possible that this economic agent defined by accounting becomes a unit of selection?

Can we define a sufficient set of characteristics, which define human behavior in market situations to design agents which are realistic mimics of human agents?

On the other hand, are there questions about markets for which the answers involve appeal to a universality class of models, where all or most of the specification of properties of agents become irrelevant? To put this differently, can we distinguish the relevant from the irrelevant parameters in microscopic models of agent interactions?

There seem to be two very distinct ways in which biology and evolution enters the discussion of economics. One, as a better understood example of a complex, self-organized system, from which ideas and strategies for economics have been drawn. Second, as a source of knowledge about how real human beings behave within markets. There does not appear to me to be a strong relation between these two claims for the relevance of biology to economics. Is this a problem?

Several times in the discussion there appeared evidence that in the real markets, at least recently, the majority of traders occupy a small number of positions in the spaces of positions and strategies. This point was made by people with experience in the markets, as well as by Sasha Outkin and Mike Brown in their discussion of the NASDAQ model. This appears to contradict the efficient market hypothesis, which holds that the market embodies all the information available to it in prices because all possible positions are taken. It is only if positions are held on all sides that equilibrium, in the sense of a static balance of opposing forces, can obtain, in a high dimensional space of products and prices. It is also only if a large number of strategies have been covered that arbitrage can be eliminated. If this it is really the case that a very small number of positions dominate markets, is this characteristic of dangerously unstable or overleveraged markets, or a general characteristic of metastable equilibria which is not captured by the efficient market hypothesis?

What are the next steps for developing this research program and field?

42 comments:

So much mathematical effort to hide the canibalistic behavior of capitalism behind numbers. This makes me want to puke. Seriously. Let me be honest to what I think: this crysis was foreseen many years ago, there is no intrisic non linearity on this, except for the disgusting fact that the biggest speculators didn't know exactly who would fail while they were manipulating everything. It's like they were the casino owners while everyone else were induced to believe they could be winning players. No one wins at gambling, except for the owner of the table.

Daniel de França said: “...this crysis was foreseen many years ago, there is no intrisic non linearity on this, except for the disgusting fact that the biggest speculators didn't know exactly who would fail while they were manipulating everything. It's like they were the casino owners while everyone else were induced to believe they could be winning players. No one wins at gambling, except for the owner of the table.”

So these “scientists”, Daniel, are also among such “owners of the table” (called “science” in this case), where formally “everybody” can play and win, but actually the winner is strictly and unconditionally predetermined from the beginning: official science is “public” only by a major source of support (unaware taxpayer money) and formal “accessibility” of its practically absent essential results (problem solutions), but in reality it is a very narrow-interest and corrupt private enterprise, much closer not even to a usual, “honest” casino, but to a “den of thieves” occupying the temple of knowledge. In other words, those “scientists” are in reality money changers, by both their dominating spirit and practice, that had usurped the power in the temple of knowledge and imposed their perverted games and self-interested purposes there. You're right, it becomes now particularly disgusting when exactly the same company of “scientists” that were there for decades, in their leading positions just in all those “advanced” and “interdisciplinary” institutes and “centres” generously supported just in exchange to equally “generous” promises to solve just those problems that turn now into a catastrophic civilisation decline (even beyond the current acute “crisis” as such) advance now quite similar, always empty promises again, so that the less they can, the more they gain (which is the core of “advanced” Obama's science politics, by the way)! Even the dirty “speculators” you denounce (equally strongly supported by the same “socially involved” administration) are less destructive than that because some of their killing “bubbles” still contributed essentially to a real development (e.g. in information and communication technologies). But scientific “owners of the table” not only did not produce anything useful (and so vitally, uniquely needed!) during the last decades, but also continue to very actively suppress any occasional possibility for genuine progress in science, necessarily beyond their disgusting and destructive business.

I would also add that all today's inflated owners (open or hidden) of the planetary tables make nevertheless one big mistake: even after all today's obvious “lessons” from reality itself, they fail to see a much greater game, where all of them, with all their “tables” and cheated treasures, is nothing but a small, inevitably losing card (together with the entire world, of course, permitting such stupid game to dominate so absolutely).

At what scale is thermonuclear fusion not positive-feedack chaotic? Whether desktop, ITER, or stellar there is no scale at which fusion is smooth and controllable. At what scale is economics not positive-feedack chaotic? Whether personal finances, corporate, or national there is no scale at which economics is smooth and controllable.

In a small reactor impose a degree of dynamic control by imposing local negative feedbacks (e.g., you cannot spend more than you have). In a large reactor it goes wild - vastly beyond any sort of administrative control. Relaxing negative feeback (cash; then escalating checks, credit cards, home equity withdrawal, insane six-figure mortgage lending, fiat $trillions created nationally) obtains increasingly violent sunspots and coronal mass ejections.

We know what happens when a massive star exhausts all its core fusion fuel into iron: photodisintegration, implosion, then supernova.

Daniel: You are missing the point. The problem is, yes, this crisis was foreseen many years ago, but it still happened. It was apparently not possible to use that knowledge in any constructive way. Why? And what can we do to avoid it in the future? There are many reasons for this failure. One problem is in the insufficiency of the models themselves, that's the issue this conference addressed. I personally think the much larger problem lies in the practice of policy making that tends to ignore academic discussions, and generally a disconnect between the organization of our political and economic systems and any sort of scientific method. Still, without scientific research any talk about the scientific method is pointless, so I think the conference aimed at an important goal. Best,

Where is psychology in all of this? Economics is the process by which humans perceive and assign value. Any economic theory that is not based on tested, reproducible psychological, behavioral, and sociological experiments will be deeply flawed.

Economics should be the statistical mechanics to Psychology's atomic physics. Continuing the analogy, current Economics is like 19 century classical physics, it is a collection of empirical laws, and we are starting to see the regimes in which these laws break down. Without conducting real experiments to probe the deeper interactions, we will never be able to move beyond the economic equivalent of the ideal gas law, no matter how sophisticated the mathematics.

it is not possible look only at the time series of prices and commodity quantities and deduce a theory. One needs to look at the fundamental driving factors of the market, which are psychological. This means one needs to know the demographics of the agents and the behaviors associated with those demographics.

For example the classic supply-demand curve describes the limiting condition of when there exists near uniformity in the perception of the agents. Fortunately such extremes rarely exist in real economies.

Even in the most desperate economies psychology is the dominate factor.

Take for example refuge camps, the food is typically only given to women - who will share and distribute; because the men will use the food to barter and coerce. If your only observable was the exchange of commodities in the camp you would not be able to deduce this relationship. Frankly, if economist ran refuge camps you would not need much of an imagination to think of the horrors that would ensue. The worst part would be that the economists would exclaim their results as a success, because they had successfully established a barter economy.

Economic theory should be based on stochastic theories of decision making, whether individual or group decisions; not the movement and pricing of commodities.

Sorry, I thought you were aiming at something completely different. Sure, you have a point there. The question is however how much psychology you really need to know, or whether it's sufficient to state there are different strategies people pursue and parametrize the frequency of their occurrence.

"One problem is in the insufficiency of the models themselves, that's the issue this conference addressed."

I did see what you mean. But what all these models do is to provide numbers and statistics to deceive people into putting money in piramides schemes. Maddoff is a small fish, I am talking about the whole stock and banking market which is mostly a giant Nigeriam scam.

Let me put this in other way, the purpose of financing the research of all these models is to elaborate a very elaborate version of Nigerian email, but in which instead of baiting naive old women, it baits economists, CEOs, and more specialists to believe that this scam is true.

And you see, what it is working here is mass manipulation schemes, this is psychology.

The goal should not be to generalize,make corections or embellish neoclassical economic theory. The goal should be to destroy its theoretical foundations and its econometric models....considering how much damage neoclassical theorists have inflicted on ordinary human beings.

So, let's take...Doyne Farmer. He would have us believe that hedge funds are crucial to the functioning of the American economy....something about smoothing out extreme price swings. Well, no one should except this at face value. Did anyone at the conference even challenge Farmer on this point?

Hedge Funds make some people very very $$$$$$thy. And with this great wealth comes great influence over the American political system. In effect, it gives a very wealthy person say like Doyne Farmer ownership of Democratic and Republican politicians. So in effect, the very wealthy hedge fund managers and their very wealty clients have life and death power over millions of Americans and human beings around the word. They can also use their wealth to set up endowed chairs in neoclassical economics. And the man or woman whose fanny occupies on of these endowed chairs gets to instruct presidents such as Barack Obama on the wonders of neoclassical economics. These wonders include such as things as Nafta, Gatt-opposed by a majority of ordinary human beings in places such as Ohio... and hundreds of Indian farmers who have taken their lives.

Something tells me that these things weren't discussed at the PI conference.

And just why are these even greater levels of mathematical abstraction even necessary? If you want to know how a particular labor market works..just go into one and talk to the laborers. That's all you really need to know.

What Aaron and some others want to say is that real-world interaction called (idiotically) “economics” is infinitely more complex than anything those “officially great” models can ever propose. Psychology - in its nationally, age-, sex-, etc. specific versions - is indeed very closely involved in “economics” and especially that of catastrophic multi-scale change called “crisis”, and as it is particularly easy to understand the complexity of this essential component (one among many others!), it is particularly relevant to demonstrate fantastic inefficiency of that kind of “rigorous” and “objective” science (dominating, nevertheless, everywhere in thus degrading world!). It's not surprising: how could one ever expect that “models” that fail to explain infinitely less complex physical phenomena (starting already from the most elementary level of fundamental physics and cosmology, where we have even greater crisis today!) could be successful in description of superior-complexity - and by all means really complex! - phenomena of interaction between many conscious beings? It's but premeditated fraud and blatant lie so characteristic of “table owners”. One can always arrange for any over-simplified model formal “agreement” with data within their limited portion (Fourier-series coefficients is a formally good, almost exact “model” of any normal function), but it becomes absolutely useless beyond that artificially arranged “success” (while that universal applicability implying predictability is the true purpose of any efficient knowledge, even beyond science). In that sense data is important, but actually it is only minor, though necessary importance: even minimally comprehensive data easily show the severe limits of all unitary science “models”, their qualitative deficiency, after which additional data accumulation becomes basically useless for essential understanding of the occurring processes (apart from mere “extrapolation” or “Fourier transform”, but such “methods” become particularly inefficient in “critical” cases, even within their “accepted” limitations).

Contrary to money for nothing in the establishment science enterprise, one cannot obtain true progress for free, without explicit, well-specified extension of knowledge. But this is just unacceptable for the establishment: do you imagine the degree of scandal if the evident deficiency of dominating “scientific” approaches and related premeditated cheating and truth suppression become as widely known as today's “economic” abuses of quite similar origin (Madoff, etc.)? It's better for them to “smoothly” direct this poor world to hell, while asking for more, ever more money for their fundamentally misleading “models”...

And any “stochastic theories” won't help, Aaron: there is nothing stochastic in psychology, even though one can, of course, artificially “average” everything, but what for, to throw off all the effects of interest? It is precisely “stochastic” way of thinking that is behind today's world crisis and decline: averaging-out kills truth in physics and progress in human society.

Yeah, they sure do average out the "noise" in the neoclassical models...the "noise" that has been made for decades by the "little" people- who can't follow line by line the thousands of proofs of economic equillibrium under different conditions using the techniques if differential topology-about the very real world consequences of neoclassical economic policy prescriptions.

I don't think complexity causes any substantial flaw in the scientific method. I do agree that in any scientific pursuit, not only is there the danger of biasing the data in favour of the hypothesis, but also the danger of biasing the hypothesis in favour of the data; there by generating a hypothesis of good utility but poor validity.

Immediately I am referring to work far more grounded, like the experiments that demonstrate how primates punish avarice, or how crows punish lying, along with human experiments that show how tokens become monetized in controlled settings.

There exists both a wealth of unexplained data in economics, and a wealth of experimental results in the cognitive sciences that can be used to construct what Bee refers to as parameterized frequencies of occurrence.

Daniel de França said: “Let me put this in other way, the purpose of financing the research of all these models is to elaborate a very elaborate version of Nigerian email, but in which instead of baiting naive old women, it baits economists, CEOs, and more specialists to believe that this scam is true.”

You are deadly exact, Daniel, in this description of the essence of modern science operation, in its both “public” and “private” versions. And of course, this humanity thus condemned to painful disappearance by its corrupt - and ultimately stupid, suicidal! - “elites” has no other possible tool to find the issue from the current impasse. It is as if “Nigerian email” (and intrinsic Nigerian development) were the only existing, absolutely dominating ways of interaction and development, while any honest exchange would be severely suppressed without discussion... Welcome to the next level...

...and how humans favour and reward both avarice and lie, (especially) in science and elsewhere... One cannot even get rid of the dominating “experiments” of this latter kind. Probably it's a sign of human “superior” origin or ... just a mistake of nature. But crows have apparently much greater chances of survival than this kind of so “developed” humanity.

I agree with Bee -- at bottom economics may be about being quantitative about psychology, but when you look at large enough groups over long enough periods of time, certain patterns emerge. This is, in fact, the explanation for the success of the rational hypothesis and neoclassical theory. To extend that theory, we need to drop the rational hypothesis and instead look directly at the patterns of behavior. Such data sets were simply not available before the internet (Csikszentmihalyi's ESM data perhaps being the exception) because humans are analog creatures, and collecting lots of data about them is time consuming and expensive.

With the correct conceptual model in mind, one can see the directionality of a change in a market without knowing exactly the magnitude of the effect. Improvements to neoclassical theory should endeavor to identify instances in which the directionality of effects predicted by neoclassical theory are violted.

I've pointed out a few of those examples in a letter I'm working on for the Federal Trade Commission in the United States, and I invite anybody interested enough to read the darn thing to send me comments.

Pretty fascinating stuff reminiscent of the Foundation Series by Isaac Asimov, where scientist Hari Seldon develops psychohistory. This brings the question of what these models are to accomplish, which is to monitor change and the implications of it or to structure change and define its limits. Like it or not this carries with it philosophical questions which as of yet haven’t been in the least dealt with by science and to a large degree ignored.

To begin with in economics as Lee points out we cannot limit ourselves to observables, yet are forced to expand this to what J.S. Bell created in physics to what is called the “beables” of a theory. These beables would not only apply to the agents observables, yet also to their own “beables” and those of the overall and developing environment. It is only with the consideration of all that we could ever hope to imagine we are accounting for what then could be described as the system. Certainly a daunting task, especially if some of the agents (variables/ beables) actually do posses what is known as free will. That is for the agents that believe in free will it will always be a concern if these models are created simply to predict outcome or rather define, limit and restrict it. To put it in the Asimov context is to ask who should we be the most wary of Hari Seldon or the Mule?

Some still seem to find it pretty convenient to think that the current crisis is but a bad but basically passing “accident on the route”, after which one can return to a “normal” operation mode, maybe even with some improvements due to better “models”. By a strange coincidence, these “optimists” tend to be just those individuals who have not only escaped any personal losses as a result of the crisis but have even acquired various “added values”, but lowering prices (with unchanged salaries), unconditionally increasing profits, sort of “crisis gifts” (American science) or inflated importance of one's otherwise useless activity. They are, in general, “well-placed”, variously “protected” and “fancy-life” individuals and communities of the replete industrial society that tend to see their dishes (ever more) full of food much better than destroyed lives of millions and billions of those “small” people that are losing everything irrespective of their own results and working efforts.

However, in the now actually unified, or “globalised”, world economy, there can be no truly “protected” areas or activities: there can be only a very ephemeral illusion of protection, in the form of artificially (and ever more unfairly) redistributed profits giving the “right” to material possessions and subjective decisions. The temporarily “spared” communities are also fatally mistaken about the meaning of the crisis: in reality it is most important not even by its direct consequences, but as a sign of the definite failure of a very large-scale and absolutely dominating “meta-model” of the world development that has no clearly specified, let alone “recognised” replacement. As a result, there is absolutely no sense to try to “improve” that definitely broken system or any its part, let alone technical details. One can only progress now by elaborating and initiating a whole new, qualitatively different and provably sustainable system (or meta-model) that cannot have anything to do with those post-modern exercises around (seriously!) proposed “economical applications” of “gauge invariance” or “quantum games”. To avoid other illusions, it cannot have anything to do with “wind-mill” kind of “energy solutions” or “climate engineering” either, these last and evidently inconsistent (but always well-paid!) fairy tales of the falling system beneficiaries that can only further amplify the decadence in case of any large-scale realisation.

It is interesting to note a very deep coherence between the falling unitary system in practical life and its externally separate version in science: in reality they are but deeply related parts of the same, now catastrophically falling monster. The crisis in imitative, bubble-based economy is only amplified by a very similar but even much stronger crisis in official science and vice versa: they have the same underlying way of thinking and the ensuing, now explicitly destructive practices. A world that wants to survive and progress should look for a suitable solution elsewhere. And a suitable solution always exists, of course, and it is even a universal and well-known one: becoming (essentially) less stupid by initiating essentially more intelligent practical solutions. It remains only to properly specify details for the present case, while avoiding any parasitic, selfish-ambition-driven imitations of the old system priests... A transparent (and unique) way to success, isn't it? So if there's anybody out there who wants to and can start it, it's better to start right now, yet before your definite understanding of being duped once more (and now forever). Nice reflections to everybody.

Looking for patterns in large populations is not science, it is signal analysis.

For Economics to be a science you have to make testable explanations for the observed data, which means understanding the mechanisms that drive markets, which are themselves the mechanisms of human decisions.

At the turn of the twentieth century the mathematics to construct quantum mechanics had been know for at least 50 years, yet it was not until the middle of the twentieth century that quantum theory was fully mathematically formulated. Why was that? It was because observations, like Rutherford scatter, radioactivity, the photo-electric effect, black body radiation, and atomic spectra, had not been made.

Deep insight requires deep observation.

While I agree economic behavior is emergent from cognitive science, that does not mean you can disregard the importance of the cognitive sciences with a justification of the law of large numbers.

Deep insight requires deep observation.I could not agree more. There are new datasets available that are making the quantitative study of large-scale human dynamics possible. In general, there seems to be a separation in time-scales between individual dynamics and the dynamics of very large groups, at least to a good approximation.

See the new paper by Duncan Watts and his colleaguse here:

http://www.technologyreview.com/blog/arxiv/23513/

That parametrized plot of the two clusters at the end -- that's a time-averaged picture of the phase space of the group's dynamics, isn't it?

Maybe I am getting cranky in my old age, but I'm going to be relentless critical.

The paper is an excellent example of a scientific hypothesis of strong utility, but little validity. Yes the authors can distinguish between distinct behaviors in the use of email, but without observing underlying demographic and sociological variables one will never be able to postulate, or test deeper hypotheses on the mechanisms that determine the observed behavior.

I'll give you a few examples of the questions they can't answer: why aren't there three groups, a third group for people who only send email after work? Does the email-aholic group mask shift workers who send email when not on shift? What about students? How will email use change as population demographics change?

It is this deeper understanding that is sought in science. Not just a good working model of reality, but a revelatory understanding of the mechanisms underlying reality.

The purpose of PI economic conference is noble, the goal credible albeit by no means easy. Dynamical economics is fundamentally different from any economic models thus far established and developing it to a form suitable for public policy will require almost super-human effort. It may take a couple of decades.

This said, my view is the current economic crash in the US (and I confine only to the US) is not a fundamental failure of 'equilibrium' economics. Yes, current economic models has many shortcomings, but most of the world uses it, including Canada, and we don't see Canada blowing up from internal economic failures like the US. Our recession is a direct result of trade dependency.

The root cause of the US crisis is intentional corruption and gaming of the economic system for the sole benefit of certain elite sectors. The intellectual justification began with the Reagan era, in the name of arresting a runaway welfare state. There is some legitimacy for this at the time. The struggle between pure state economics and pure private economics is a healthy one, providing checks and balances. Equilibrium economic management has no trouble adjusting to this political struggle for economic balance within the capitalist system. It has worked for many decades, requiring occasional 'fine tuning'.

But what happened this time was that the struggle for balance was broken, replaced by a fundamentalist ideology, which then proceeded to go to extreme. It is therefore no surprise that those who won in this fundamentalist ideology are the same people who gamed the system for immense profits, leading to a complete corruption of the entire political, economic, financial, central banking, trading and rating systems. Even a large portion of the corporate business model was rotted - the famous CEO compensation being one measure.

With such madness, NO economic model, equilibrium or dynamical, can work to prevent it. But, alas, it is working now to account for it. (I won't go so far to say it is fixing it.) Because all the immense gains, the stratospheric 'wealth' created during the past decade, has been wiped out. Everything going back to a more equilibrium state. Leaving behind untold human misery. Nothing fixes like a good dose of misery. Like Germany after WW2. I am sure Bee can say something about that!

I believe that what's missing from mainstream economic theory is a good model of bubbles. The mainstream belief is that bubbles are not possible, because if one were to form, each economic agent would rationally choose not to participate, i.e. they would anticipate that the bubble will eventually (unpredicably) burst. And yet bubbles happen...

The bursting of a bubble is very disruptive to the economy, so what we need is an economic early warning indicator that a bubble is developing, so that actions can be taken to deflate it before it gets too big.

"The mainstream belief is that bubbles are not possible, because if one were to form, each economic agent would rationally choose not to participate, i.e. they would anticipate that the bubble will eventually (unpredicably) burst. And yet bubbles happen..."

This belief has been proven false by Mandelbrot in 1966:http://www.e-m-h.org/Mand66.pdf

Not correct. The mainstream belief, if one can use Mr Greenspan as representative of that mainstream, is it is useless, and certainly not the job of a central bank, to arrest the formation of a bubble. Bubbles can most certainly form, and have formed many times in recent past. Mr Greenspan belief is it is up to the private market to self-regulate and burst the bubble; it is up to the central bank to contain the damage once it has burst. But it is not the task of government, nor that of central bank, to 'manage' economic bubbles.

One of the key motivations of dynamical economics is to model the formation of bubbles, and to manage them. It is almost like managing nuclear fission.

Tkk, You disagree with my thesis that mainstream economists don't believe in bubbles, and bring up Greenspan as an example. Perhaps I should have said "mainstream economists don't believe that you can detect bubbles". In Greenspan's recent testimony to Congress, he said that his large staff of of Ph.D.s were unable to forecast the decline in housing prices - i.e. they did not recognize that a bubble was being formed and would soon burst. He also made a statement to the effect that such forecasting is impossible, saying that if it were possible to forecast a housing decline, then arbitragers would jump in - the usual argument.

He also said that we probably need new approaches to modeling..

Here's the link:http://oversight.house.gov/story.asp?ID=2261

Skip forward to about 140 minutes into the testimony, and also about 170 minutes into it.

Perhaps that Shows that Greenspan is a lier and doesn't care about anything except for his pockets. That is, all his career is made of spreading lies, numbers and promoting pseudo scientific theories to deceive people (even the rich and billionaires) into investing in whatever he thought he could drag into his pyramid scheme. People like him are the lowest scum of this planet, because not even by seeing his lack of morals, people believe on the crap they say. Madoff is an angel compared to the likes of Greenspan.

Daniel,"Perhaps that Shows that Greenspan is a lier and doesn't care about anything except for his pockets."

I can't believe that there was any maliciousness involved in this crisis. All the actors were simply doing their jobs with the tools at hand, and those tools have been found wanting.

The Wall street banks were exploiting an opportunity: they could create a lot of synthetic "AAA" securities out of subprime mortgages by the magic of traunching. The rating agencies were using generally accepted methodologies for rating those traunches using historical loss rates, which were low. The returns on those AAA traunches were higher than the returns on government bonds, creating huge demand, which triggered more origination of mortgages, which pushed up the price of houses, which caused default rates to go even lower (people who were in trouble could borrow on their rising equity to pay the interest), bringing us back to the beginning in a positive loop - in other words a bubble.

This may be a gross oversimplification, but in any case I don't think that the Fed had the tools to recognize that something like this was happening. Almost nobody did. Those tools now need to be developed.

Anonymous:"I should have said "mainstream economists don't believe that you can detect bubbles"

Not a question of believing in the possibility or detection of bubble. They believe you can't manage them. Because there are no workable tools, and the outcome all but unpredictable due to almost lack of understanding. This is a key reason of the PI economic conference - to develop models and tools for dynamical (i.e. bubbly) economics.

Daniel:"Perhaps that Shows that Greenspan is a lier ..."

I am no fan of Greenspan but perhaps the very harsh words you threw at him a bit too much. Roubini in his conference presentation (I attended the first day) criticized Greenspan in the harshest words I have heard from an economist. He said Greenspan ignored decades of literature on the formation and characters of bubbles. Thus guilty of being an incompetent economist. He said Greenspan believes the self-interests of market players will automatically regulate bubbles without causing systemic crisis. Roubini called this thinking fundamentally stupid. Calling the former chairman of the Federal Reserve, the "Mestro", incompetent and stupid is truly devastating. Perhaps that should be enough.

I am pleased that courageous physicists and mathematicians now acted to contribute to developing a new more accurate economic model. This is a positive outcome of this very tragic state of affair.

All this talk about bubbles is to suggest that economics represents being simply another name for risk assessment, which would be disappointing if true. That is it ignores the role motivation and vision plays in all of this. It seems to me the best that can be expected of such thinking is to find more reason not to attempt things, rather than reasons we should. Economics also has concepts like risk capital for instance, which if one examines things closely enough much of our innovation and real growth depend on.

I would ask what all of this brain storming is going to do as it relates to this aspect of economic development and planning. It’s easy to say someone should be held responsible for not realizing we were living above our means and forget the whole system is based on not what we can manage safely now, yet what we could in future achieve. The best that government can do is to enrich the soil and control the weeds as they have little or no idea what this preparation and care will yield. For me all these models seem no better than being able to predict what we get when seeds are left to the fate and mercy of the winds. If this truly is all it amounts to in the end these models will have failed to grasp the capacity and potential of what it’s attempting to understand.

Tkk:"They believe you can't manage them. Because there are no workable tools.."

I'm more inclined to think the problem is in detection. If a bubble had been detected, the Fed could have done something, and it wouldn't have required increasing interest rates. They have the power to force banks to do "stress tests". They could force them to hold some of the securities that they are selling (as Greenspan is now advocating), and to increase the required capital, etc. They have a lot of power over the financial system.

Arun:"Grant's Interest Rate Observer knew what was happening, why could not the Fed?"

I guess the problem here is with having conviction. In his testimony to congress, Greenspan said something like "there are always people saying that there is a big problem, but half the time they are wrong. So what are we to do?" What is lacking is a model of bubbles that officials can have confidence in, so that they can act upon the signals.

There's a real opportunity here, and I would urge the organizers of the "Economic Manhattan Project" to work closely with the regulators.